PREA: Personalized Recommendation Algorithms Toolkit

Recommendation systems are important business applications with significant economic impact. In recent years, a large number of algorithms have been proposed for recommendation systems. In this paper, we describe an open-source toolkit implementing many recommendation algorithms as well as popular evaluation metrics. In contrast to other packages, our toolkit implements recent state-of-the-art algorithms as well as most classic algorithms. [abs] [ pdf ][ bib ] [ code ] &copy JMLR 2012. ( edit, beta )

Authors

• Joonseok Lee Google Research Seoul National University
• Mingxuan Sun Louisiana State University
• Guy Lebanon

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